Current oscilloscopes can display images of waveforms derived from an internal image which may possess a large dynamic range of pixel intensities. Although the variation in pixel intensity of the internal image may be large, the actual display of this image limits the intensity range and therefore does not fully reflect all of the information contained in the internal image. An example of an oscilloscope which illustrates this problem is disclosed in U.S. Pat. No. 5,986,637 entitled DIGITAL OSCILLOSCOPE ARCHITECTURE FOR SIGNAL MONITORING WITH ENHANCED DUTY CYCLE, issued to Etheridge et al. The Etheridge et al. device increases the percentage of time that an input signal is actively monitored in an attempt to detect and ultimately display rare, anomalous and nonrepetitive events.
Etheridge et al. illustrates the fact that as acquisition technology improves, greater dynamic range of the internal image intensity is created from the increased number of signal acquisitions incorporated into a single waveform image. However, due to limitations in existing display technology it is not possible to display this enhanced dynamic range. Current oscilloscopes typically deliver only sixteen levels of dynamic range in brightness to the user. Future oscilloscopes will probably present a brightness range of 64 or more (i.e., 256) levels.
Since the displayable dynamic range is limited, the desired goal is to extract the maximum intensity variation and hence the maximum signal information from the internal waveform image. Ideally, a method to automatically and fully utilize the available, limited dynamic range of the display, and a machine to implement that method, is needed. Histogram equalization is a known image processing method for increasing contrast and utilizing dynamic range in an image. An example of such image processing is disclosed in U.S. Pat. No. 5,995,656 entitled IMAGE ENHANCING METHOD USING LOWPASS FILTERING AND HISTOGRAM EQUALIZATION AND A DEVICE THEREFORE, issued to Kim. By adjusting the intensities of an image such that the histogram of image intensities is flat, the best representation of the full dynamic range of intensities present in the image is realized.
Intensity adjustment allows many pixels of similar intensities, which were previously displayed in a similar manner, to appear with differing intensities, allowing the user to discern additional signal detail from the intensity variations. A histogram is a representation of the relative distribution of the intensities appearing in an image. FIG. 1, for example, is a typical input histogram 35 that results from a television sweep signal. The histogram 35 creates a series of compartments or columns, such as regions 17, 18, 19 and 20, each of which represents a subset or range of potential pixel intensities present in the image. The intensity of each pixel is examined and is assigned to the appropriate histogram column or “bin” which matches the detected intensity. If there is an even distribution of intensities in an image, the histogram is therefore “level” or “equalized” because bin counts are the same. As seen in FIG. 1, the histogram 35 is typically uneven, with most of the measured pixel intensities being grouped near bins 17, 18 and 19 with virtually no picture elements residing in region 20 or beyond.
Referring also to FIG. 2, a transfer function 242 is depicted which may be applied to the raw input image histogram of FIG. 1. The transfer function 242 includes numerous discrete break points or transitions 21, 22, 23, 24, 25, 26, 27, 28, 30 and 31 which define, in this case, a series of linear transfer functions of varying slopes. By applying an input image to the transfer function 242, the output histogram 33 depicted in FIG. 3 is produced. While the distribution of intensities has been improved, there are still regions such as 4, 5, 14 and 15 which include relatively large amounts of data while regions 6, 11, 12 and 16 contain relatively little image data. Thus a substantially flat output histogram has not been obtained, which is typical when using a discrete histogram equalization system. Referring also to FIG. 11, a representative image 240 produced by a typical prior art oscilloscope is shown. The regions 233, for example are primarily blue in color while regions 234 are primarily green, with very few other colors present. The viewer of such an image is left to wonder if the image 240 represents the actual waveform being measured or is primarily an artifact of the oscilloscope signal processing circuitry.
Programmable mapping machines exist that can be used to transfer an image having a large dynamic range to a display having a small dynamic range, such as is disclosed in U.S. Pat. No. 5,909,244, entitled REAL TIME ADAPTIVE DIGITAL IMAGE PROCESSING FOR DYNAMIC RANGE REMAPPING OF IMAGERY INCLUDING LOW LIGHT VISIBLE IMAGERY, issued to Waxman et al. This device can implement linear mapping or a gamma corrective mapping.